Why 3VR FailedBy John Honovich, Published Feb 16, 2018, 10:10am EST
3VR destroyed transformed ~$65 million in VC funding into a $6.9 million exit.
The reason they failed is simple. They bet on analytics. They lost.
The reason they bet on analytics is simple too. It is the same reason that Object Video bet on it in 2001 and Hikvision is betting on it in 2018. If you make it work, it has clear huge value.
But the more interesting question is: how did 3VR handle the problems? Obviously, they knew long before their firesale to Identiv that analytics had big problems. What did they try to do? Why did they not try other things? What lessons can be learned?
As someone who was on the inside during the early stages (2005 - 2007, first as Director of Systems Engineering, then as Director of Product Management), my goal is to share some perspective and ideas that might help illuminate the issues involved.
Positive - Lots of Smart People
One thing that certainly was not an issue was talent. 3VR had an abundance of talented people. The stereotype of Silicon Valley as a center for talent certainly proved true. One issue was a lack of experience in the surveillance industry but that was far less of a problem that not being able to deliver 3VR's core value proposition.
Problems Scaling - Demos vs Deployments
A key challenge 3VR experienced, and something still an issue today for many analytics companies, is a false sense of confidence from demos and small systems vs problems in larger production systems.
Like any analytic startup, 3VR started using their analytics in small areas - their own office with their own employees and people coming by for meetings (investors, prospects, etc.). With a small number of people to be analyzed and key engineering people to set things up precisely, 3VR worked pretty well inside 3VR's office. Likewise, in smaller beta and early deployments, especially with friendly customers, it 'mostly' worked.
The real problem came when 3VR's facial recognition started to be deployed in larger public sites (e.g., hotels or multiple bank branches). They had lots more people, lots more restrictions on where cameras could be placed, challenges in how people moved (large hallways, turns, etc.). This combined resulted in dramatically worse performance and false alerts / matches.
A major internal problem that resulted from this was a debate about why these results were so much worse. For example, many at HQ were understandably confused or skeptical about the problems in the field.
Pessimists vs Optimists
Obviously now, it is easy to look back and see the 'pessimists' (not surprisingly, myself included) were right. In fairness to the optimists, it was not as clear back then. It could have field errors and even if it was not that, the technology could have possibly improved so much in the next few years that the issues would be resolved.
On the other hand, after carefully analyzing various field results, key engineering people knew the problems faced and that eliminating them was far beyond any reasonable short to mid-term action. And, as the last decade showed, this is still a challenging problem today.
CEO Steve Russell - Great and Terrible
Enter CEO Steve Russell. Russell was simultaneously great and terrible.
He was incredible at getting people excited and convincing people things could be done. An incomparable pitchman, he combined self-confidence, humor, and intelligence in an extremely rare combination. One of the most amazing things he would do is talk about all levels of technology and technical details, but unlike engineers, he would say it confidently and without hesitation nor examining exceptions. This was terrific for a startup because when hard things came up (like facial recognition), he had great answers.
The problem was that he was terrible at understanding and accepting reality. While he sounded great talking about technology, after a while, you began to realize that Russell was engaging in wishful thinking, at best and science fiction, at worst. This was a huge problem, especially when 3VR faced real customer problems because Russell's reaction was to explain it away or offer some unrealistic but impressive sounding non-solution.
Engineering's Russell Rule
A great example of this was an informal 'Russell Rule' that the engineers had that no engineer should speak to Russell for more than 5 minutes. Russell was really good, in a bad way, at asking individual engineering specialists about specific problems, probing them to admit some way could be found. Then, the engineer, nervous not to offend the CEO, might agree, "well, maybe it's possible to do it that way", even though that was a theoretic possibility, not something 3VR could practically do in the foreseeable future.
Product Estimation Chaos
Related, there were comical product planning challenges with Russell. His estimates were consistently incredibly lower than others. Engineering leaders might estimate 6 weeks for a feature, I might say a month, Russell would say 3 days. He'd then pull out a white paper or article he read and explain how easy it was, while the exasperated engineering leaders tried in vain to explain why that was not realistic. This was, while funny at one level, a real problem for the company.
The Problem With Russell (and the Board's) Unrealistic Expectations
During the 2005 - 2007 time frame, as the company scaled up and expanded into more production deployments, 3VR undoubtedly faced significant performance problems. The debate was what to do.
Russel, and via Russell's great salesmanship, the board was sold on analytics and facial recognition as a game changer. The problem was 3VR could not deliver it in practice.
Selling Search vs Alerts
One common technique that 3VR tried to use was to emphasize selling search (i.e., 3VR is Google for video surveillance). So just like Google is not always perfect in giving a first result match and that does not matter, likewise 3VR would do the same. This, theoretically, would free 3VR from the much harder technical constraints of doing accurate facial surveillance alerts.
The sales problem was that video surveillance customers valued alerting far more than searching. Even if you steered customers to search, most would gravitate towards alerting and almost none would pay anywhere near the premium for better searching than they would for alerting.
Half Pivot To Recorder / Wells Fargo
3VR, to its credit, did at least half pivot to be a 'smart recorder'. While, at first, 3VR was facial surveillance with a few recorder features, 3VR did recognize that they needed to do both (facial + recorder) to win deals. And with a heroic effort by 3VR's then-junior but very talented salesperson Matt Vallone [link no longer available], plus engineering delivering dozens of fundamental recorder features, 3VR won Wells Fargo, 3VR's all-time largest customer and source of 30%+ of 3VR's total revenue.
Never Reached Product / Market Fit With Face
The problem, though, was that face recognition and other analytics never reached a point of performance where they could drive mass adoption. It increasingly became clear that 3VR was a solid recorder with some neat analytics that may or not be used, a no man's land in terms of growth.
No Pivot to Software Only / 'Just' A VMS
Two other important problems existed. These would not have been problems if face / analytics worked well, but without that, 3VR was left to fight against other recorders / VMS.
3VR was against software only for many years, only selling appliances, including the prime years where Genetec and Milestone were rapidly gaining ground. There were concerns about supporting customers. In retrospect, the decision clearly hurt the company.
Related, 3VR management was aware of the growth of the 'plain' non-analytic VMSes like Exacq, Genetec and Milestone. 3VR certainly had the money and the engineering talent to compete in that area. The problem was one of CEO and board expectations. To really focus and fight those VMS companies, 3VR would have to sacrifice development and focus on analytics which was something that they did not have the drive to do, simply it would have been effectively admitting failure. Of course, now, 3VR selling for $6.9 million in 2018, pivoting to be 'just' a VMS certainly would have delivered greater returns but the CEO and VCs would prefer to strike out going for a home run.
Leave to Do IPVM
I left in 2007 / 2008. While I did not know what I was going to do next, outside of programming on my own, that evolved into IPVM. And IPVM's critical coverage of marketing and analytics was definitely impacted and motivated by the challenges at 3VR.
The New CMO
The most notable 3VR exec to leave in that same time period was sales and marketing co-founder Tim Ross [link no longer available], who while a Silicon Valley native, was a realist and balance to Rusell.
3VR's next marketing leader Aisling MacRunnels [link no longer available] was a stereotypical over-confident Silicon Valley exec. Despite being in the industry weeks, she lectured me about how analytics were so hot and how I (now running IPVM) did not understand the market. MacRunnels lasted 16 months at 3VR.
The New CEO
One of the strangest parts of 3VR was their hiring of Al Shipp [link no longer available], who had an impressive resume as an exec at Apple, stayed at 3VR for nearly a decade, overseeing its decline into this sorry ending. As an outsider, I am not sure what he was doing or thinking all that time.
Happy Ending For Russell
Lest anyone think everything here is negative for Russell, there is a happy ending for him. On the downside, he started another analytics company, Prism, that also has struggled. But, he was also friends or housemates with Garrett Camp who founded Uber. Russell put some money in early and, now, he has made far more on that than he is likely to make on his 2 analytic startups.
Given the constraints 3VR was operating under, specifically, the CEO and board's desire to go big and difficulty accepting the real challenges faced, it is not clear what could have been done.
However, trying as best as possible to understand the real problems a company face head-on, without excuses or wishful thinking, can result in properly changing direction to find a better outcome, even in a bad situation.
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